Blood pump system and method of operation

ABSTRACT

A blood pump system includes a blood pump having a motor with a rotor and a stator. The stator has a plurality of stator windings situated therein. A motor controller is coupled to the motor, and a processor has inputs coupled to the motor controller for receiving a time continuous signal from the pump. The processor is programmed to transform the time continuous signal to the frequency domain, and control the pump and detect excess suction in response to the time continuous signal in the frequency domain.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.10/675,669, (Sep. 30, 2003), now U.S. Pat. No. 7,396,327, issued Jul. 8,2008. U.S. application Ser. No. 10/675,669 is a continuation-in-part ofInternational Application No. PCT/US03/20268 (Jun. 26, 2003), which is anon-provisional of U.S. Provisional Application No. 60/319,358 (Jun. 26,2002); International Application No. PCT/US03/18859 (Jun. 13, 2003),which is a non-provisional of U.S. Provisional Application No.60/319,318 (Jun. 14, 2002); International Application No. PCT/US03/00516(Jan. 8, 2003), which is a non-provisional of U.S. ProvisionalApplication No. 60/346,555 (Jan. 8, 2002); and International ApplicationNo. PCT/US03/00273 (Jan. 7, 2003), which is a non-provisional of U.S.Provisional Application No. 60/346,721 (Jan. 7, 2002). Each of theapplications referenced above is incorporated herein by specificreference.

BACKGROUND

1. Field of the Disclosure

The disclosure relates generally to blood pump systems, and morespecifically, to a method and system for control of such pumps.

2. Description of Related Art

Generally, blood pump systems are employed in either of twocircumstances. First a blood pump may completely replace a human heartthat is not functioning properly, or second, a blood pump may boostblood circulation in patients whose heart is still functioning althoughpumping at an inadequate rate.

For example, U.S. Pat. No. 6,183,412, which is commonly assigned andincorporated herein by reference in its entirety, discloses a ventricleassist device (VAD) commercially referred to as the “DeBakey VAD™.” TheVAD is a miniaturized continuous axial-flow pump designed to provideadditional blood flow to patients who suffer from heart disease. Thedevice is attached between the apex of the left ventricle and the aorta.Proper blood flow through the device depends on an adequately filledventricle and a positive differential pressure between the inlet and theoutlet of the VAD pump.

Known blood pump systems typically are controlled in an open loopfashion where a predetermined speed is set and the flow rate variesaccording to the pressure differential across the pump. The pump itselfmay be controlled in a closed loop fashion, wherein the actual pumpspeed is fed back to a motor controller that compares the actual speedto the desired predetermined speed and adjusts the pump accordingly.However, prior art closed loop control systems—varying the pump speed inresponse to a monitored physiologic parameter—have largely beenunsatisfactory.

Moreover, since the VAD produces flow continually and actively fills, ithas the potential to create low pressure at the inflow in order toproduce flow. “Excess Suction” occurs when the pressure in the inflowcannula decreases significantly—the pump begins to “suck” the ventricleclosed, which would greatly reduce the pumping capability of the nativeheart and VAD. Decreasing the VAD's speed during an excess suctioncondition would allow the ventricle to refill, and normal blood flow toresume. Additionally, the detection of ventricular collapse and theability to automatically adjust the pump's speed may aid in maintainingcorrect blood flow to the patient.

Excess suction may be caused by occlusion of the tip of the inflowcannula or by completely emptying the ventricle (ventricular collapse).In known pump systems, sustained excess suction typically triggers adiagnostic alarm on the pump controller. However, it would be desirableto detect the onset of suction prior to any physiological effect.Additionally, it is typical of known methods that attempt to detect theonset or presence of ventricular collapse to use a binary “suctiondetect” flag when the onset of suction is believed to have beendiscovered. Information in addition to a simple binary indicator,however, is desirable as it would allow a physician or technician tomake a more precise diagnosis.

The present invention addresses shortcomings associated with the priorart.

SUMMARY OF THE DISCLOSURE

In one aspect of the present disclosure, a blood pump system includes ablood pump having a motor with a rotor and a stator. The stator has aplurality of stator windings situated therein. A motor controller iscoupled to the motor, and a processor has inputs coupled to the motorcontroller for receiving time continuous signals from the pump, such asflow, current, speed, etc. The processor is programmed to transform thetime continuous signal(s) from the time domain to the frequency domain,and control the pump and to detect excess suction in response to thetime continuous signal in the frequency domain.

The time continuous signal may include the stator winding current, thepump speed or the pump voltage, for example. In certain embodiments, theblood pump system includes a flow measurement device coupled to theprocessor for providing a signal representing the pump flow rate,wherein the time continuous signal may also include the pump flow rate.

In accordance with additional aspects of the disclosure, the processormay also be programmed to determine and output parametric data (meanvalues of flow, speed, heart rate, etc.) based on the sampled timecontinuous signal in the frequency domain. For example, heart rate maybe derived from the frequency domain representation of the flow data. Toobtain the desired resolution of the heart rate calculation withinrequired time limits, the sampled time continuous signal may be zeropadded. Still further, the processor may be programmed to validateintegrity of the sampled time continuous signal based on the sampledtime continuous signal in the frequency domain. This validation mayinclude calculating the signal to noise ratio and/or the signal to noiseplus distortion ratio.

In accordance with still further aspects of the disclosure, the pumpsystem includes an analog to digital converter that converts the timecontinuous signal to a digital signal. A sample mode selector isconnected to the analog to digital converter for selecting one of asynchronous sample mode or an asynchronous sample mode. If theasynchronous sample mode is set, the sampling rate of the analog todigital converter is set by a reference clock, and if the synchronoussample mode is set, the sampling rate of the analog to digital converteris set according to the frequency of the time continuous signal.

BRIEF DESCRIPTION OF THE DRAWINGS

Other objects and advantages of the invention will become apparent uponreading the following detailed description and upon reference to thedrawings in which:

FIG. 1 schematically illustrates various components of an implantablepump system in accordance with embodiments of the present invention.

FIG. 2 is a cross-section view of an exemplary implantable pump inaccordance with embodiments of the present invention.

FIG. 3 is a block diagram illustrating aspects of a controller module inaccordance with embodiments of the present invention.

FIG. 4 is a block diagram conceptually illustrating a pump controlsystem in accordance with embodiments of the present invention.

FIG. 5 illustrates exemplary physiologic control modes in accordancewith aspects of the present invention.

FIG. 6 is a graph showing another control mode in accordance withaspects of the present invention.

FIGS. 7A-7E illustrate additional aspects of physiologic control modesin accordance with aspects of the present invention.

FIGS. 8 and 9 are block diagrams conceptually illustrating methods ofdetecting ventricle collapse in accordance with embodiments of thepresent invention.

FIG. 10 is a block diagram illustrating further aspects of the exemplarypump control system shown in FIG. 4.

FIGS. 11 and 12 illustrate a “normal” flow waveform (no excessivesuction) in the time and frequency domains, respectively.

FIGS. 13 and 14 illustrate a distorted flow waveform (due to suction) inthe time and frequency domains, respectively.

FIGS. 15 and 16 illustrate time domain representations of flow generatedbased on a sampling of a time continuous data using 10% and 90% zeropadding, respectively.

FIGS. 17 and 18 are frequency domain representations corresponding tothe time domain representations shown in FIGS. 15 and 16, respectively.

While the invention is susceptible to various modifications andalternative forms, specific embodiments thereof have been shown by wayof example in the drawings and are herein described in detail. It shouldbe understood, however, that the description wherein of specificembodiments is not intended to limit the invention to the particularforms disclosed, but on the contrary, the intention is to cover allmodifications, equivalents, and alternatives falling within the spiritand scope of the invention as defined by the appended claims.

DETAILED DESCRIPTION OF THE INVENTION

Illustrative embodiments of the invention are described below. In theinterest of clarity, not all features of an actual implementation aredescribed in this specification. It will of course be appreciated thatin the development of any such actual embodiment, numerousimplementation-specific decisions must be made to achieve thedevelopers' specific goals, such as compliance with system-related andbusiness-related constraints, which will vary from one implementation toanother. Moreover, it will be appreciated that such a development effortmight be complex and time-consuming, but would nevertheless be a routineundertaking for those of ordinary skill in the art having the benefit ofthis disclosure.

Turning to the figures, FIG. 1 illustrates a ventricle assist device(VAD) system 10 such as disclosed in U.S. Pat. No. 6,183,412, which iscommonly assigned and incorporated herein by reference in its entirety.The VAD system 10 includes components designed for implantation within ahuman body and components external to the body. Implantable componentsinclude a rotary pump 12 and a flow sensor 14. The external componentsinclude a portable controller module 16, a clinical data acquisitionsystem (CDAS) 18, and a patient home support system (PHSS) 20. Theimplanted components are connected to the controller module 16 via apercutaneous cable 22.

The VAD System 10 may incorporate an implantable continuous-flow bloodpump, such as the various embodiments of axial flow pumps disclosed inU.S. Pat. No. 5,527,159 or in U.S. Pat. No. 5,947,892, both of which areincorporated herein by reference in their entirety. An example of ablood pump suitable for use in an embodiment of the invention isillustrated in FIG. 2. The exemplary pump 12 includes a pump housing 32,a diffuser 34, a flow straightener 36, and a brushless DC motor 38,which includes a stator 40 and a rotor 42. The housing 32 includes aflow tube 44 having a blood flow path 46 therethrough, a blood inlet 48,and a blood outlet 50.

The stator 40 is attached to the pump housing 32, is preferably locatedoutside the flow tube 44, and has a stator field winding 52 forproducing a stator magnetic field. In one embodiment, the stator 40includes three stator windings and may be three phase “Y” or “Delta”wound. The rotor 42 is located within the flow tube 44 for rotation inresponse to the stator magnetic field, and includes an inducer 58 and animpeller 60. Excitation current is applied to the stator windings 52 togenerate a rotating magnetic field. A plurality of magnets 62 arecoupled to the rotor 42. The magnets 62, and thus the rotor 42, followthe rotating magnetic field to produce rotary motion.

FIG. 3 conceptually illustrates aspects of the pump system 10. Morespecifically, portions of the controller module 16 and the pump 12 areshown. The controller module 16 includes a processor, such as amicrocontroller 80, which in one embodiment of the invention is a modelPIC16C77 microcontroller manufactured by Microchip Technology. Themicrocontroller 80 includes a multiple channel analogue to digital (A/D)converter, which receives indications of motor parameters from the motorcontroller 84. Thus, the controller module 16 may monitor parameterssuch as instantaneous motor current, the DC component or mean value ofthe motor current, and motor speed.

The embodiment shown in FIG. 3 further includes an integral flow meter86. At least one flow sensor 14 is implanted down stream of the pump 12.Alternately, a flow sensor 14 may be integrated with the pump 12. Theflow meter 86 is coupled between the implanted flow sensor 14 and themicrocontroller 80. The flow meter 86 receives data from the flow sensor14 and outputs flow rate data to the microcontroller 80, allowing thesystem to monitor instantaneous flow rate.

Since the implanted flow sensor 14 is coupled to the flow meter 86 ofthe controller module 16, a true measure of system performance (flowrate) is available for analysis, in addition to pump parameters such asmotor speed and current (power). Further, since the flow meter 86 is anintegral component of the controller module 16, flow rate may bedisplayed on the controller module display and flow rate data may besaved in the controller module memory.

In exemplary embodiments of the invention, the motor controller 84comprises a MicroLinear ML4425 Motor Controller. The operation of thebrushless DC motor 38 of the present invention requires that current beapplied in a proper sequence to the stator windings 52 to create therotating field. Two stator windings 52 have current applied to them atany one time, and by sequencing the current on and off to the respectivestator windings 52, the rotating magnetic field is produced. In anembodiment of the invention, the motor controller 84 senses back electromotive force (EMF) voltage from the motor windings 52 to determine theproper commutation phase sequence using phase lock loop (PLL)techniques. Whenever a conductor, such as a stator winding 52, is “cut”by moving magnetic lines of force, such as are generated by the magnets62 of the brushless DC motor 38, a voltage is induced. The voltage willincrease with rotor speed 42. It is possible to sense this voltage inone of the three stator windings 52 because only two of the motor'swindings 52 are activated at any one time, to determine the rotor 42position.

An alternative method of detecting the rotor 42 position relative to thestator 40 for providing the proper stator winding 52 excitation currentsequence is to use a position sensor, such as a Hall Effect sensor oroptical encoder. Implementing aspects of the present invention using amotor with rotor position sensors, rather than a sensorless motor, wouldbe a routine undertaking for one skilled in the art having the benefitof this disclosure. However, adding additional components, such as Halleffect sensors, requires additional space, which is limited in anyimplanted device application. Further, using a position detection deviceadds sources of system failures.

The motor controller 84 operates to maintain the pump 12 at anessentially constant speed regardless of the differential pressureacross the pump or the flow through the pump. As noted above, the motorcontroller 84 uses PLL to control the speed of the pump motor 38(commutation control). An additional analog closed-loop control circuitcontrols the onboard pulse width modulator (PWM) to maintain a desiredspeed setting. Both control-loops work in unison to maintain properspeed control.

The motor controller 84 forms a PLL with a voltage-controlled oscillator(VCO), back-EMF sampling error amplifier, loop-filter, sequencer, andoutput driver. The motor controller 84 samples the instantaneous motorphase that is not energized to determine whether to increase or decreasethe commutator (VCO) frequency. The VCO generates an output frequency(commutation rate) proportional to input voltage. A late commutationcauses the error amplifier to charge the loop filter, increasing the VCOinput while early commutation causes the error amplifier to dischargethe loop filter, decreasing the VCO input. The PWM loop, operating atapproximately 25 kHz in exemplary embodiments, effectively maintains thedesired speed setting once the PLL has reached steady-state (the desiredtarget speed). Constant speed control of the three-phase pump motor,under varying or pulsatile load conditions, is achieved by varying theamount of current delivered to the stator windings proportionally to themotor's load.

The commutation and PWM loops have, because of their associated filternetworks, individual frequency and time domain responses associated withthem. The frequency range over which the loop system will follow changesin the input frequency is called the lock-in range. The frequency rangeover which the loop acquires phase-lock is the capture range, and is, inthis system, less than the lock-in range.

The dynamic characteristics of the phase-locked loop, and thus the waythe pump motor responds to changes in load, are controlled primarily bythe loop filter. The filter network included in the PLL serves two majorfunctions. First, it removes any noise and high-frequency componentsfrom the error amplifier's output providing an average (dc) voltage tobe fed to the VCO's input, and it is the primary element that determinesthe dynamic performance of the loop including capture (pull-in) range,lock-in range, bandwidth, and transient response.

Once the loop is phase-locked, the filter limits the speed of the loopto track changes in the input frequency (motor speed). In addition, theloop filter provides a “flywheel” effect, ensuring a rapid recapture ofthe signal if the system is thrown out of lock by a noise transient.

Variations in differential pressure across the pump 12 will impartinstantaneous changes in pump's load, which will further result in aninstantaneous change in the speed of the pump motor 38. The motorcontroller 84 will sense this change in speed through its back-EMFsampler and attempt to speed up or slow down the pump motor 38, suchthat the preset speed is maintained. This instantaneous load change andcorresponding correction performed by the motor controller 84 willresult in a corresponding variation in the pump's current (power), speedand flow waveforms. An instantaneous increase in the pump's load willcause an instantaneous decrease in pump speed and thus an instantaneousincrease in pump current (power) and decrease in flow rate. Conversely,an instantaneous decrease in the pump's load will cause an instantaneousincrease in pump speed and thus an instantaneous decrease in pumpcurrent (power) and increase in flow rate.

Therefore, the pump's current (and therefore power), speed, and flowwaveforms correlate well with changes in the pump's load. Thesewaveforms may be used to calculate the patient's heart rate,instantaneous and mean blood flow rate, regurgitant flow, instantaneousand mean power consumption, the pump's efficiency (e.g. dQ/dn or dQ/dP),etc. These waveforms also indicate when the pump's speed is set too highand the ventricle begins to collapse. This condition exists when theflow and/or current waveforms are highly-asymmetric and/or their peaksappear to contain multiple ripples or are flattened (clipped).Additionally, waveforms with short negative rise-times (attack) followedby slower positive exponential fall-times (decay) indicate suction.

The aforementioned signals, current (power), speed, and flow, aretime-continuous band-limited signals. The current signal is a compositesignal containing the motor controller's PWM frequency, the patientsheart rate (assuming there is a heart rate), and other frequenciesrelating to certain physiologic responses within the patient'scardiovascular system (e.g. respiratory rate, valve openings andclosures, changes in systemic resistance, etc.). The pulse-widthmodulation frequency typically is approximately 25 kHz and the patient'spulse rate is approximately 0.7 Hz to 4.0 Hz (i.e. BPM (beats perminute) to 240 BPM). A two-pole maximally flat low-pass ButterworthFilter (f_(c)=250 Hz) within the controller module 16 may be used tolimit the bandwidth of this signal.

The power signal is the product of the pump motor current and pump motorvoltage (a constant scalar) and is therefore a composite signal which,like the current, contains the motor controller's pulse-width modulation(PWM) frequency, the patient's heart rate (assuming there is a pulserate), and other frequencies relating to certain physiologic responseswithin the patient's cardiovascular system (e.g. respiratory rate, valveopenings and closures, changes in systemic resistance, etc.). Thepulse-width modulation frequency is approximately 25 kHz and thepatient's pulse rate is approximately 0.7 Hz to 4.0 Hz (i.e. 40 BPM to240 BPM).

The speed signal typically contains the heart rate of the patient(assuming there is a native heart rate) as the dominant frequency alongwith other frequencies related to certain physiologic responses withinthe patient's cardiovascular system (e.g. respiratory rate, valveopenings and closures, changes in systemic pressure, etc.). The angularmomentum of the rotor impeller and viscosity of the blood dampen abruptchanges in speed and thus the bandwidth of this signal is typicallybelow 30 Hz.

The flow signal typically contains the heart rate of the patient(assuming there is a native heart rate) as the dominant frequency alongwith other frequencies related to certain physiologic responses withinthe patient's cardiovascular system (e.g. respiratory rate, valveopenings and closures, changes in systemic pressure, etc.). A two-polemaximally-flat Butterworth Filter (f_(c)=30 Hz) within the controllermodule 16 limits the bandwidth of this signal.

Variations in the flow, speed, current, and power waveforms in the timedomain will result in corresponding variations in their frequency domainrepresentations. The frequency domain representations for these signalsmay be obtained through the application of the Discrete FourierTransform (DFT) or the Fast Fourier Transform (FFT), though the FFT ismore efficient computationally than is the DFT and is generally moreeasily realized in hardware and/or software. Continuous conversion ofthese time continuous physiologic signals from the time domain to thefrequency domain provides real-time spectral content information aboutthese signals.

In accordance with exemplary embodiments of the present invention,methods and mechanisms are presented, through use of the DFT and/or FFT,to provide simultaneous physiologic control of the pump 12, signalvalidation and ventricular suction detection in the frequency domainusing a single data set. FIG. 4 is a block diagram conceptuallyillustrating an integrated pump control system 100 in accordance withaspects of the present invention.

The control system 100 may be implemented in software, hardware, or acombination thereof. Software implementations include using themicrocontroller 80 provided in the controller module 16. Alternatively,a stand-alone microcontroller or a digital signal processor (“DSP”), forexample, may be used. Exemplary hardware implementations may include afield programmable gate array (“FPGA”), a complex programmable logicdevice (“CPLD”), application specific integrated circuits (“ASIC”),discrete analog and/or digital components, etc.

A time continuous physiologic signal 101 (flow rate, current, etc.) isreceived from the pump 12 and/or flow sensor 14. The time continuoussignal 101 is then transformed to the frequency domain in block 102. Thefrequency domain representation 102 of the sampled signal 101 is thenused for simultaneous physiologic control 103 of the pump 12 and suctiondetection 104.

FIG. 5 illustrates three exemplary physiologic control modes 103 inaccordance with aspects of the present invention that employ suctiondetection and physiologic “triggers”: “constant speed” 311, “constantflow” 312, and “maximize, or maximal, flow” 313. These control modes areshown via a plot of flow rate vs. pump speed. In the constant speed mode311, the pump speed remains constant with changes in flow rate and inthe constant flow mode 312, the flow rate remains constant as the speedvaries. The constant speed mode is suitable, for example,intraoperatively, while weaning the patient off cardiopulmonary bypass,following surgery, and when the patient is discharged from the hospital.As noted above, the pump is operated at a fixed, predetermined speed.The speed may be optionally adjusted in response to suction events—i.e.,the pump speed may be reduced in response to detected suction events.The constant flow mode is suitable, for example, for patients inintensive care (ICU), recovery or during weaning from bypass.

The maximize, or maximal, flow mode 313 is suitable, for example, duringrecovery or during exercise. With the maximize flow mode 313, the pumpspeed is periodically increased until a “diminishing returns” point isreached, and/or until another predetermined limit is reached (i.e.maximum power, maximum pump speed, etc.). In other words, the controllerincreases pump speed to a point at which an increase in pump speed nolonger produces a corresponding increase in flow or a correspondingdecrease in peak-to-peak amplitude. The maximize flow mode may bemanually enabled by the patient, for instance, via a push button at thestart of exercise, or it may be automatically triggered in response to apredetermined parameter.

FIG. 6 shows a control mode in which the desired flow rate is generallyproportional to a linear interpolation of heart rate. Desired rest andexercise flow rates are established, and in the illustrated mode, thedesired flow rates do not go below or above these rates, respectively,regardless of the heart rate. Between the rest and exercise heart rates,the desired flow rate varies with heart rate.

FIG. 7 provides additional aspects of the constant speed, constant flowand maximize flow, as well as a “constant peak-to-peak amplitude” mode.In some implementations, the physician may select which control mode isthe most appropriate for the patient. The means to enable a true“physiologic” response is via a trigger—for example, diastolic flow orheart rate, or a combination of the two, as identified in theincorporated applications. Alternatively, a manual trigger, such as an“exercise” button on the controller 16 may be used. The physician mayselectively enable or disable the exercise button or the automatictriggers and may selectively decide if flow will be maximized by“diminishing returns” (change in flow for a given change in speed) ormaximized by “minimal peak-to-peak amplitude” (the flow pulsatility, orpeak-to-peak amplitude, decreases as pump speed is increased)

If the desired flow for the patient cannot be achieved (e.g. a boundarycondition is reached such as maximum speed, maximum power, or minimumpulsatility), then pump speed is not adjusted further. In otherimplementations, the control mode may be changed and the pump speed isreduced to achieve a desired peak-to-peak amplitude. In the controlmodes shown in FIG. 7, suction detection is either enabled or disabledbut the corresponding alarm remains active. In other embodiments,varying levels of “ventricular unloading” are employed, assuming thatthe risk for suction is greatest with lower flow pulsatility.

Control parameters for each of the control modes are summarized anddescribed in FIG. 7. For example, in the constant speed control modeshown in FIG. 7A, a clinician enters values for parameters shown inbold—the desired pump speed and the minimum flow rate. The values shownin regular type (not in bold) are default values that can be manuallychanged by the clinician. Additionally, the clinician enables ordisables the “suction detection” and “suction detection response”parameters. If the suction response is enabled, upon detection ofsuction, the controller 16 activates a diagnostic alarm and reduces thepump speed by a predetermined amount and rate until suction disappears.For a suction-triggered speed reduction, the controller is programmed towait a predetermined amount of time, then increase the speed by apredetermined amount and rate until the nominal speed is again achieved.If suction is detected again and the speed is reduced in responsethereto (prior to achieving the nominal speed), the controller repeatsthe delay and subsequent speed increases. If suction is detected a thirdtime with a corresponding speed reduction prior to achieving the nominalspeed, the speed increase process repeats with a slower time period. Atone or other audible or visual signal is activated when the nominalspeed is achieved. If the suction response is disabled, the diagnosticalarm is activated but no additional automatic responses are executed.If either the minimum speed or minimum flow is reached, the controlleractivates a diagnostic alarm and the speed is not reduced any further.

If the signal from the flow meter 86 (or Flow Sensor Board, FSB) is notreceived or is corrupted, for example, a “bad flow signal” flag is set.In response to the detection of a poor flow signal, the controller 16activates a diagnostic alarm, the speed setting is not changed, and theFSB is reinitialized. If the flow signal is still considered unusable orinvalid, the controller 16 reinitializes the FSB periodically andsuppresses the low flow alarm. If the flow signal returns (i.e.considered to be valid), the controller 16 reverts back to the desiredcontrol mode, if the desired mode is other than the constant speed mode.Similarly, if a poor quality flow signal is received, the controller 16activates a diagnostic alarm, maintains the current speed setting andsuppresses the low flow alarm. If the pump reaches the maximum powerlevel, a diagnostic alarm is activated.

In the constant flow mode shown in FIG. 7B, the desired flow rate isentered, and the maximum power and minimum flow parameters may becalculated based on the desired flow rate from the characteristicflow-pressure curves of the pump. The remaining parameters are defaultvalues that may be manually changed by the clinician. Upon detection ofsuction, the controller 16 activates a diagnostic alarm and reducesspeed by a predetermined amount and rate until the suction disappears.If the minimum speed or minimum flow level is reached, the controller 16activates a diagnostic alarm and does not reduce the speed any further.

For a suction-triggered speed reduction, the controller 16 is programmedto wait a predetermined amount of time, then increase the speed by apredetermined amount and rate until the nominal flow is again achieved.If suction is detected again, and the speed is reduced in responsethereto (prior to achieving the nominal flow), the controller 16 repeatsthe delay and subsequent speed increases. If suction is detected a thirdtime, with a corresponding speed reduction prior to achieving thenominal flow, the speed increase process repeats. The system may also beprogrammed to adaptively respond to suction events. The suction indicesdescribed herein provide continuous real-time indications of the degreeof suction (i.e. 0% to 100%) and thus, the higher the index value, thegreater the probability of suction. Therefore, the system may bedesigned to reduce the pump's speed by an amount proportional to thedegree of suction (i.e. a higher suction index yields a greater speedreduction than a lower suction index). A tone or other signal isactivated when the nominal flow is achieved. If a bad flow signal orpoor flow signal quality is received, the controller activates adiagnostic alarm and reverts to the constant speed control mode, withthe speed set at “FSB fail speed”—typically 9000 RPM or the fail-safespeed, 8500 RPM. If the maximum power threshold setting is reached, thecontroller 16 activates a diagnostic alarm and the speed is not allowedto increase further. If the maximum speed setting is reached, adiagnostic alarm is activated and the speed is not increased above themaximum speed value.

In the constant peak-to-peak amplitude mode shown in FIG. 7C, theminimum flow parameter is entered and control is based on thepeak-to-peak amplitude (“P2P”) of the flow signal. The remainingparameter values are defaults that can be manually changed by theclinician. If suction is detected the controller 16 activates adiagnostic alarm and reduces speed by a predetermined amount and rateuntil the desired peak-to-peak amplitude is achieved. If the minimumspeed or minimum flow setting is reached, the controller 16 activates adiagnostic alarm and does not reduce speed any further.

In the event of a suction triggered speed reduction, the controller 16waits a predetermined amount of time, then increases speed by apredetermined amount and rate until the nominal peak-to-peak amplitudevalue is achieved. If, prior to reaching the nominal peak-to-peakamplitude, a suction triggered speed reduction occurs again, the speedincrease is repeated after a predetermined time period. If a suctiontriggered speed reduction occurs a third time, the speed increase isrepeated at a slower repetition rate. The controller 16 activates a toneor other signal when the nominal peak-to-peak amplitude is achieved. Ifa “bad” flow signal or poor quality flow signal quality is received, thecontroller 16 activates a diagnostic alarm and reverts back to theconstant speed control mode, with the speed set at the FSB fail speed.If the maximum speed or power threshold levels are reached, thecontroller activates a diagnostic alarm and the speed is not increasedfurther.

FIGS. 7D and 7E summarize the maximize flow algorithms based onpeak-to-peak amplitude (pulsatility) or diminishing returns (change inflow vs. change in pump speed). The maximize flow mode is either enabledor disabled via settings on the CDAS 18. If the maximize flow mode isenabled, then either the peak-to-peak amplitude (P2P) or point ofdiminishing returns (dQ/dn) algorithm must be selected. Once themaximize flow mode is selected, the various triggers (e.g. diastolicflow, heart rate or exercise, for example) are individually enabled ordisabled. In the illustrated embodiments, the maximize flow modes do not“branch to any other modes; they may only return to the original controlmode.

In the “maximize flow” control mode, based on peak-to-peak amplitude,the controller varies speed to maintain constant peak-to-peak amplitudeof the flow signal. The peak-to-peak amplitude value may be dependent onthe desired degree of ventricular unloading (for example, low, medium,high). If excess suction is detected, the controller activates adiagnostic alarm, reduces speed by some predetermined rate (200 RPM inone implementation) per second until suction disappears, waits 15seconds, then attempts to servo to peak-to-peak amplitude.

The maximize flow mode based on diminishing returns is summarized inFIG. 7E. Speed is increased a predetermined amount and rate until thedesired dQ/dn is achieved. Periodically, speed is increased to checkdQ/dn. The speed is then decreased, and if the dQ/dn does not vary, thecontroller continues to decrease the speed. In other words, the speed isalways increased once, then decreased twice, then the controller waits apredetermined amount of time. If excess suction is detected, thecontroller 16 activates a diagnostic alarm and reduces speed at apredetermined rate until the suction disappears. The controller thenwaits a predetermined amount of time, and then repeats the dQ/dnroutine.

With either the peak-to-peak amplitude or diminishing return modes, ifthe minimum speed setting is reached, a diagnostic alarm is activatedand the speed is not reduced further (i.e. constrained in hardware forsafety). If the minimum flow value is reached, the controller 16activates a diagnostic alarm, the speed is not reduced further, and thecontroller reverts back to original control mode. If the maximum speedor power value is reached, the controller 16 activates a diagnosticalarm and does not increase the speed any further. If a bad flow signalis received, the controller 16 activates a diagnostic alarm and revertsto the original control mode. The “baseline” flow is the mean flow priorto entering the maximize flow control mode. If the “Allow Flow BelowBaseline” 15 is enabled, the minimum flow threshold is a percentage ofthe baseline flow (baseline flow * predetermined percentage ofbaseline). The default setting for flow is “Not allowed below baseline”.

In exemplary embodiments, the minimum speed limit is 7.5 kRPM, and themaximum speed limit is 12.5 kRPM. The hardware fail-safe speed is 8.5kRPM. The bad flow signal or poor flow signal quality set speed (“FSBfail speed”) is 9.0 kRPM. The controller module 16 indicates which modeis active, and also indicates whether peak-to-peak amplitude or“diminishing returns” is selected for the maximize flow algorithm andwhich triggers are active. The controller 16 further includes an“Exercise” button that is illuminated anytime the maximize flowalgorithm is activated. In certain embodiments, the controller 16 isprogrammed such that the patient can defeat the maximize flow algorithmby holding the Exercise Button for a predetermined length of time, whichalso functions to defeat the automatic triggers for some predeterminedtime period.

In accordance with embodiments of the invention, the excess suctionoperation 104 uses spectral analysis equations to process the frequencydomain data representation and generate suction probability indexes.These spectral analysis equations include analyses based on harmonicdistortion, total spectral distortion (harmonic distortion and noise),sub-fundamental distortion (distortion below the fundamental frequency),super-fundamental distortion (distortion above the fundamentalfrequency), the ratio of the super-fundamental distortion to thesub-fundamental distortion, super-physiologic distortion (distortion atfrequencies above the assumed maximum physiologic fundamentalfrequency—typically 4 Hz or 240 BPM), and the spectral dispersion or“width” of the resulting flow(f) waveform. These spectral analysistechniques are addressed in detail as follows.

The spectral distortion factor measures the ratio of all energycontributed by all frequencies about the fundamental frequency withrespect to the fundamental frequency. A higher distortion ratioindicates a higher probability of suction.

${{Spectral}\mspace{14mu} {distortion}\mspace{14mu} {factor}} = \frac{\left\lbrack \sqrt{{\sum\limits_{n = 1}^{x}\left\lbrack {A\left\lbrack f_{({n \cdot {dF}})} \right\rbrack} \right\rbrack^{2}} - \left\lbrack {A\left\lbrack f_{1} \right\rbrack} \right\rbrack^{2}} \right\rbrack \cdot 100}{{A\left\lbrack f_{1} \right\rbrack}}$

wherein n indicates the spectral component's index/position in theresulting array; x is the last index/position in this array; dFrepresents the frequency resolution/interval of the resulting DFToperation in Hertz; and f_(l) is the fundamental frequency, the maximum(amplitude) spectral peak in the DFT resultant array. Since the spectralanalysis of the flow rate signal pertains to the AC component, and notthe mean value or offset, the range of interest does not include n=Obecause the mean flow rate or DC component of the flow(f) waveformoccurs at n=O. This is true for all of the frequency domain suctionprobability indices contained herein.

The harmonic distortion factor measures the ratio of energy contributedby all harmonics about the fundamental frequency with respect to thefundamental frequency.

${{Harmonic}\mspace{14mu} {distortion}\mspace{14mu} {factor}} = \frac{\left\lbrack \sqrt{\sum\limits_{n = 2}^{x}\left\lbrack {A\left\lbrack f_{n} \right\rbrack} \right\rbrack^{2}} \right\rbrack \cdot 100}{{A\left\lbrack f_{1} \right\rbrack}}$

wherein n indicates the n^(th) harmonic in the resulting array; x is thehighest harmonic in this array; f_(l) is the fundamental frequency, themaximum (amplitude) spectral peak in the DFT resultant array; and f_(n)represents integer multiples of the fundamental f_(l) from n=2 (secondharmonic) to x (x^(th) harmonic).

The sub-fundamental distortion factor measures the additive frequencycontributions below the fundamental frequency with respect to thefundamental frequency.

${{Sub}\text{-}{fundamental}\mspace{14mu} {distortion}\mspace{14mu} {factor}} = \frac{\left\lbrack \sqrt{\sum\limits_{n = 1}^{{n{({f\; 1})}} - 1}\left\lbrack {A\left\lbrack f_{({n \cdot {dF}})} \right\rbrack} \right\rbrack^{2}} \right\rbrack \cdot 100}{{A\left\lbrack f_{1} \right\rbrack}}$

wherein n indicates the spectral component's index/position in theresulting array; dF represents the frequency resolution/interval of theresulting DFT operation in Hertz; f_(l) is the fundamental frequency,the maximum (amplitude) spectral peak in the DFT resultant array; andn(fl) is the index/position of the fundamental.

The super-fundamental distortion factor measures the additive frequencycontributions above the fundamental frequency with respect to thefundamental frequency.

${{Super}\text{-}{fundamental}\mspace{14mu} {distortion}\mspace{14mu} {factor}} = \frac{\left\lbrack \sqrt{\sum\limits_{n = {{n{({f\; 1})}} + 1}}^{x}\left\lbrack {A\left\lbrack f_{({n \cdot {dF}})} \right\rbrack} \right\rbrack^{2}} \right\rbrack \cdot 100}{{A\left\lbrack f_{1} \right\rbrack}}$

wherein n indicates the spectral component's index/position in theresulting array; x is the last index/position in this array; dFrepresents the frequency resolution/interval of the resulting DFToperation in Hertz; f_(l) is the fundamental frequency, the maximum(amplitude) spectral peak in the DFT resultant array; and n(fl) is theindex/position of the fundamental.

The super/sub fundamental distortion factor measures the ratio ofadditive frequency contributions above the fundamental frequency to theadditive frequency contributions below the fundamental frequency.

${{Super}\text{/}{sub}\mspace{14mu} {fundamental}\mspace{14mu} {distortion}\mspace{14mu} {factor}} = \frac{\left\lbrack \sqrt{\sum\limits_{n = {{n{({f\; 1})}} + 1}}^{x}\left\lbrack {A\left\lbrack f_{({n \cdot {dF}})} \right\rbrack} \right\rbrack^{2}} \right\rbrack \cdot 100}{\left\lbrack \sqrt{\sum\limits_{n = 1}^{{n{({f\; 1})}} - 1}\left\lbrack {A\left\lbrack f_{({n \cdot {dF}})} \right\rbrack} \right\rbrack^{2}} \right\rbrack}$

wherein n indicates the spectral component's index/position in theresulting array; dF represents the frequency resolution/interval of theresulting DFT operation in Hertz; x is the last index/position in thisarray; and n(fl) is the index/position of the fundamental.

The super physiologic distortion factor measures the additive frequencycontributions above the maximum expected physiologic frequency (i.e. 4Hz=240 BPM) with respect to the fundamental frequency.

${{Super}\mspace{14mu} {physiologic}\mspace{14mu} {distortion}\mspace{14mu} {factor}} = \frac{\left\lbrack \sqrt{\sum\limits_{n = {{n{(f_{b})}} + 1}}^{x}\left\lbrack {A\left\lbrack f_{({n \cdot {dF}})} \right\rbrack} \right\rbrack^{2}} \right\rbrack \cdot 100}{{A\left\lbrack f_{1} \right\rbrack}}$

wherein f_(h) is a spectral peak at frequency=4 Hz; n indicates thespectral component's index/position in the resulting array; x is thelast index/position in this array; dF represents the frequencyresolution/interval of the resulting DFT operation in Hertz; fi is thefundamental frequency, the maximum (amplitude) spectral peak in the DFTresultant array.

In other embodiments, the spread of the waveform is measured. As notedabove, it is assumed that a physiologically appropriate waveform in thetime domain is quasi-sinusoidal at a single frequency proportional tothe patient's native heart rate, and hence, the correspondingphysiologically appropriate waveform in the frequency domain will be asingly narrow spectral peak at the same single frequency proportional tothe patient's native heart rate. Deviations from this quasi-sinusoidalcase may indicate suction as well as other defects.

For example, as the flow(t) waveform becomes more distorted, the flow(f)waveform will contain additional flow contributions at varyingfrequencies and will thus begin to “widen”. The probability that suctionis imminent or present increases proportionally to the width of flow(f).The measure of the width of flow(f) about the fundamental frequency isthe square-root of the mean-squared variation about the fundamentalfrequency. The spectral dispersion factor measures the “width of theflow(f), current(f), speed(f), and/or power(f) signals:

${{Spread}\mspace{14mu} {Flow}} = \frac{\sqrt{\sum\limits_{n = 1}^{N}\left\lbrack {{A\left\lbrack f_{({n \cdot {dF}})} \right\rbrack} - {A\left\lbrack f_{1} \right\rbrack}} \right\rbrack^{2}}}{N}$

wherein f_(l) is the fundamental frequency, the maximum (amplitude)spectral peak in the DFT resultant array; dF represents the frequencyresolution/interval of the resulting DFT operation in Hertz; n indicatesthe spectral component's index/position in the resulting array; and N isthe last index/position in this array. Since the analysis of spread flowis concerned with the wave shape, and not the offset, the range ofinterest does not include n=0 because the mean flow rate or DC componentof the flow(f) waveform occurs at n=0.

Some alternatives to applying the spectral content of the measuredsignal to spectral analysis equations are shown in FIGS. 8 and 9, wherethe real time spectral content measured signal is compared to apredetermined spectral mask. In the embodiment shown in FIG. 8, thespectral content 420 generated by the DFT 412 is compared to apredetermined spectral mask 422 in a combiner block 424. In block 426,the presence of suction is determined based on the comparison. Thesignals whose spectral components fall within the mask indicate suctionand, conversely, signals whose spectral components fall outside the maskindicate normal flow.

In the embodiment shown in FIG. 9, the time domain responses areconverted to frequency domain through the application of a synchronousswitched-capacitor filter 430. In this exemplary embodiment, thefrequency response of the filter 430 is controlled by a clock source onehundred times the desired pass-band frequency. A phase-locked loop 432generates this clocking signal to the filter 430 by receiving the outputfrom a zero crossing detector 434 and multiplying the incomingfundamental frequency by an integer multiplier 436, the value of whichis selected by a digital input element such as a microcontroller.Incrementing the integer multiplier will cause the synchronous filter to“track” the incoming signal and output the spectral amplitude of thefundamental frequency, first harmonic, second harmonic, etc. The sum ofthe individual spectral amplitudes results in a frequency-domainrepresentation of the time-domain signals.

As in the embodiment illustrated in FIG. 8, a comparison may then bemade between the real-time spectral content 420 of these signals and thepredetermined spectral mask 422. Signals whose spectral components fallwithin the mask indicate suction and, conversely, signals whose spectralcomponents fall outside the mask indicate normal flow.

Additionally, the frequency domain representation 102 may be used tovalidate the integrity of the sampled signal 101. The signal validationprocess 105 may provide an output to an “enable” setting 107 of the pumpcontrol process 108. Still further, real-time extraction of parametricdata, such as the patient's heart rate, respiratory rate and pump flowinformation may be derived from the frequency domain representation 102and output to a user interface display 106.

FIG. 10 is a block diagram illustrating further aspects of the pumpcontrol system 100 in accordance with an exemplary embodiment of thepresent invention. The time continuous physiologic signal 101 isrestricted below the Nyquist frequency using a low pass antialiasingfilter 112. An analog-to-digital converter 114, which may be clockedasynchronously or synchronously based on a mode select input 116 to asampling mode selector 118, is then used to convert the signals intodigital values.

If the asynchronous sampling mode is selected, a fixed timebasereference clock 120 provides the sampling timing source. If thesynchronous sampling is selected, a PLL is used to synchronously samplethe applied signal 101. After filtering, the applied signal 101 is sentto a signal shaper 122 and a phase detector 124, and the resultantsignal is low-pass filtered 126 and provided to a voltage controlledoscillator 128. The synchronous sampling rate is set by a frequencymultiplier 130, based on an integer multiple M of the fundamentalfrequency of the applied signal 101. For example, if M=100, the appliedsignal 101 will be sampled at a rate proportional to 100 times thefundamental frequency of the applied signal 101. Synchronous sampling,although more complex to implement, minimizes spectral leakage fromoccurring in the DFT's output array, and enables a more accurate measureof frequency/amplitude information near the fundamental.

The digital signals from the analog-to-digital converter 114 are storedinto an input memory buffer 140 of length N for processing by the DFTengine 142. The size of the input memory buffer 140 is governed by thenumber of points N to be processed by the DFT 142, the amplituderesolution of the samples, the system's sampling rate, and the desiredDFT output frequency resolution. An output memory buffer 144 containshalf as many points as that of the input memory buffer 140 (N/2) and isused to store the array resulting from the DFT 140, containing thesingle-sided spectrum of the transformed signal.

A “normal” flow waveform (no excessive suction) is quasi-sinusoidal(after filtering). FIGS. 11 and 12 illustrate such a waveform in thetime 210 and frequency 212 domains, respectively. This exemplary flowsignal was sampled with f_(s)=100 Hz and processed using the DFT withN=500 points. The frequency domain representation of the signal 212contains the instantaneous mean flow rate 214 along with a singleadditional prominent peak 216 located at a frequency 218 in hertzcorresponding to the patient's heart rate in beats per minute divided by60 seconds/minute. The peak 216 indicates the patient's heart rate andthe peak-to-peak flow rate.

FIGS. 13 and 14 illustrate a distorted flow waveform due to suction inthe time 220 and frequency 222 domains, respectively. As with the normalsignal shown in FIGS. 11 and 12, the exemplary flow signal shown inFIGS. 13 and 14 was sampled with f_(s)=100 Hz and processed using theDFT with N=500 points. The frequency domain representation 222 of thesignal contains the instantaneous mean flow rate 224, and multipleadditional peaks located at a frequency proportional to the patient'sheart rate and harmonics thereof. The peak 226 indicates the peak flowrate at the fundamental frequency 228, with additional peaks 230 atharmonics of the fundamental frequency 228. Transient suction events maycontain additive frequency components which are not harmonically relatedto the fundamental frequency.

As rioted herein above, the frequency domain representation 102 of thetime continuous signal may be used to provide real-time parametric data,such as the patient's heart rate, and output to a user interface display106, stored for later analysis, etc. Of course, an accurate heart ratedetermination can be critical to proper control of the pump system 10and to the general management of a patient.

For example, determination of heart rate to ±1.5 BPM may be desired.Frequency resolution using the DFT or FFT algorithm is defined by thedata sampling rate f_(s) and the total number of samples to be processed

$N\text{:}{\frac{f_{s}}{N}.}$

This relationship indicates that the frequency resolution may beincreased either by decreasing the data sampling rate or by increasingthe total number of data points to be processed. The sampling rate f_(s)must be sufficiently high to preserve the fidelity of the sampled flowsignal (i.e. >60 Hz) and the number of samples N must be sufficientlylow such that a new heart rate value is calculated in a timely fashion,for example, every one or two seconds.

In order for the FFT algorithm to calculate a heart rate value with anaccuracy of 1.5 BPM at a typical sampling rate f_(s)=100 Hz, 4096 datasamples (N=4096) would be required. However, it would take 40.96 secondsto acquire 4096 samples with f_(s)=100. Thus, sampling 4096 data pointsclearly does not provide the required timeliness.

“Zero padding” consists of extending the sampled data with zeros toextend its time limits. It maps a length N signal to a length M signal,where M>N. To quickly and accurately determine heart rate, a relativelysmall data sample N is used, with the remaining time continuous signalsample points being zero padded. For example, one or two seconds ofactual sampled time continuous data may be used to allow heart ratecalculation within the desired time frame, resulting in 100 to 200 datapoints at f_(s)=100 Hz. The remaining 3896 to 3996 data points are zeropadded to provide a quick and accurate heart rate calculation. A furtherincrease or decrease in resolution may be obtained by increasing ordecreasing the value of N, respectively. For example, a resolution of ±1BPM may be obtained by using N=6000 data points with fs=100 Hz. In thisinstance, one to two seconds of actual time continuous data would besampled, with 5800 to 5900 zero padded data points.

FIGS. 15 and 16 are time domain representations, and FIGS. 17 and 18 arecorresponding frequency domain representations generated based on asampling of a time continuous flow waveform using 10% and 90% zeropadding, respectively. The flow waveform files upon which theillustrated frequency domain representations were based contained 4096data points processed with the FFT algorithm. The synthesized signalused for this analysis was a sine wave sampled at fs=100 Hz with a meanflow rate of 3 liter/min, a peak-to-peak amplitude (pulsatility) of 6liter/min, and a frequency of 1.772 Hz (106.3 BPM—a typical heart ratefor a blood pump recipient). As noted above, the frequency resolution ofthe FFT algorithm is

$\frac{f_{s}}{N}.$

Hence, the pulse rate resolution corresponding to these parameters is±1.5 BPM.

As shown in FIGS. 17 and 18, the frequency resolution of the FFTalgorithm in the frequency domain remains constant with 10% and 90% zeropadding of the time domain data. Additional side lobes are generatedwith increased zero padding which further results in amplitudedistortion at the fundamental frequency. However, the fundamentalspectral component—which is proportional to heart rate—remains the mostprominent in the FFT's resultant array. Since the objective is todetermine heart rate, the amplitude distortion may be ignored and thecorrect heart rate may be obtained.

By using a single frequency domain representation of the sampled timecontinuous signal, a complete pump control system may be implementedonto one integrated circuit including signal validation, physiologiccontrol, suction detection, motor control, and determination ofparametric data such as heart rate.

The particular embodiments disclosed above are illustrative only, as theinvention may be modified and practiced in different but equivalentmanners apparent to those skilled in the art having the benefit of theteachings herein. Furthermore, no limitations are intended to thedetails of construction or design-herein shown, other than as describedin the claims below. It is therefore evident that the particularembodiments disclosed above may be altered or modified and all suchvariations are considered within the scope and spirit of the invention.Accordingly, the protection sought herein is as set forth in the claimsbelow.

1-31. (canceled)
 32. A method of controlling a blood pump, comprising:sampling a time continuous signal from the blood pump to obtain a firstnumber of data points; transforming a second number of data pointsrelating to the sampled time continuous signal to the frequency domain,wherein the second number is greater than the first number; analyzingthe sampled time continuous signal in the frequency domain; controllingthe blood pump in response to the analysis of the sampled timecontinuous signal in the frequency domain; and detecting excess suctionin response to analysis of distortion in the sampled time continuoussignal in the frequency domain.
 33. The method of claim 32, furthercomprising determining parametric data in response to the analysis ofthe sampled time continuous signal in the frequency domain.
 34. Themethod of claim 33, wherein the parametric data includes heart rate. 35.The method of claim 33, wherein the parametric data includes respiratoryrate.
 36. The method of claim 33, wherein the parametric data includespump flow rate.
 37. The method of claim 32, wherein sampling the timecontinuous signal from the blood pump includes sampling betweenapproximately 100 and 200 data points of the time continuous signal. 38.The method of claim 32, further comprising zero padding the first numberof data points to obtain the second number of data points.
 39. Themethod of claim 32, further comprising validating the sampled timecontinuous signal in response to the analysis of the sampled timecontinuous signal in the frequency domain.
 40. The method of claim 39,wherein validating the sampled time continuous signal includesevaluating the signal to noise ratio.
 41. The method of claim 39,wherein validating the sampled time continuous signal includesevaluating the signal to noise plus distortion ratio.
 42. The method ofclaim 32, wherein the time continuous signal is selected from the groupconsisting of a pump flow rate, a pump speed, and a pump current. 43.The method of claim 32, wherein the time continuous signal is selectedfrom the group consisting of a pump inlet pressure, a pump outletpressure, and a differential pressure across the pump.
 44. A blood pumpsystem, comprising: a blood pump comprising a rotor and a stator, thestator including a plurality of stator windings; a controlleroperatively coupled to the pump; a processor operatively coupled to thecontroller and adapted to receive a first number of data points relatingto a time continuous signal from the pump; and wherein the processor isprogrammed to transform a second number of data points relating to thetime continuous signal to the frequency domain, wherein the secondnumber is greater than the first number, and to detect excess suction inresponse to distortion in the transformed time continuous signal. 45.The blood pump system of claim 44, wherein the controller appliescurrent to the stator windings in a sequence to create a rotating field,and wherein the time continuous signal includes one or more statorwinding current.
 46. The blood pump system of claim 44, furthercomprising a flow measurement device coupled to the processor andproviding a signal representing the pump flow rate, wherein the timecontinuous signal includes the pump flow rate.
 47. The blood pump systemof claim 44, wherein the processor is programmed to zero pad a digitalrepresentation of the received time continuous signal.
 48. The bloodpump system of claim 47, wherein the digital representation of thereceived time continuous signal from the blood pump comprises betweenapproximately 100 and 200 data points of the time continuous signal. 49.The blood pump system of claim 44, wherein the processor is programmedto zero pad the first number of data points to obtain the second numberof data points.
 50. The blood pump system of claim 44, wherein the timecontinuous signal is selected from the group consisting of a pump flowrate, a pump speed, and a pump current.
 51. The blood pump system ofclaim 44, wherein the time continuous signal is selected from the groupconsisting of a pump inlet pressure, a pump outlet pressure, and adifferential pressure across the pump.